The present invention relates generally to estimation of aircraft flight data, utilizing a neural network receiving inputs based on parameters measured or determined in a fixed reference frame, and is related to the disclosures in U.S. Pat. Nos. 5,751,609, 5,890,101 and 5,901,272.
Air vehicles are designed for a wide variety of missions. Fighter and attack aircraft can operate at high speed and perform high-g maneuvers while helicopters operate primarily at lower speeds and perform maneuvers such as those associated with anti-submarine warfare, vertical replenishment, and search and rescue missions. Tiltrotor and tilt-wing aircraft have the capability to takeoff and land vertically but also achieve higher forward speeds than traditional helicopters. For all of these different types of aircraft, reliable airspeed data is required to maintain proper control of the aircraft. For fly-by-wire systems, airspeed in particular can be critical, with loss of the airspeed measurement resulting in the possibility of the aircraft going unstable.
Traditional airspeed systems consist of pressure sensors designed to measure total air pressure as well as static pressure as the aircraft moves through the air mass. Traditional air data sensors are costly and expensive to calibrate and maintain. Such airspeed systems must also be rugged enough to operate reliably in the harsh environment encountered by military aircraft. It is therefore an important object of the present invention to estimate airspeed by use of a low-cost, software-based approach.
In addition, traditional airspeed systems are not accurate when the resultant velocity is at a significant angle to the measurement probe. Therefore, when the aircraft nose is pointed in a direction substantially different from the direction in which the aircraft is moving, as in sideslipped or high angle of attack flight, the traditional airspeed sensor can be inaccurate. It is therefore another important object of the present invention to obtain data as to when an aircraft is operating at significant angles of attack and sideslip, by use of low cost means for determining airspeed, sideslip and angle of attack.
In accordance with the present invention, a system for simply, accurately and economically estimating aircraft flight data is provided using input parameters derived in the fixed reference frame of the aircraft fuselage. Specific examples of such flight data include aircraft airspeed, sideslip and angle of attack. Existing flight sensors can be used for measurement and supply of fixed frame parameters to a neural network through which the flight data estimates are calculated. The flight parameters can be further processed to provide indications to the pilot and ground crew of dangerous flight conditions such as stall, loss of tail rotor effectiveness and vortex ring state.